Modelling emergency disaster mortality around the world: a network-based distributional inference approach

2025/09/03 by Alessandro Spelta, Paolo Pagnottoni, Nicoló Pecora · 1 voice · 1 citation
Medicine · Social Sciences · Health Professions · #Data-Driven Disease Surveillance #Disaster Management and Resilience #Disaster Response and Management

paper · doi:10.1093/jrsssa/qnaf140

openalex publication_date 2025/09/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

Abstract In this paper, we leverage Optimal Transport theory and network analysis to propose a novel distributional framework for the inference of mortality risks arising from worldwide emergency disasters. We propose a propagation method grounded on Wasserstein barycentre and similarity networks, based on climate, social, economic, and demographic variables, able to model mortality risk distributions, when country-level information is incomplete or unavailable. We apply our proposal to the International Emergency Events Database showing that the method is able to coherently reconstruct the mortality risk distributions related to natural and technological disasters via the information embedded in country similarity networks. We provide a comprehensive indicator of countries potential extreme losses from various types of disasters through the Gini-based Value-at-Risk (Gini-VaR). This measure provides country-specific and disaster-specific probabilistic impacts of extremely severe hazards. We also shed light on the relationship between disaster risk preventive strategies put in place by nations and their mortality risk profiles based on the Gini-VaR, highlighting major inequalities across countries.

Citations

• New Orleans Business Recovery in the Aftermath of Hurricane Katrina
• A Review on Multi-Label Learning Algorithms
• A Survey on Transfer Learning
• Inference for extreme spatial temperature events in a changing climate with application to Ireland
• Multifidelity Computer Model Emulation with High-Dimensional Output: An Application to Storm Surge
• Inference for Empirical Wasserstein Distances on Finite Spaces
• A regional compound Poisson process for hurricane and tropical storm damage

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Discussions

• "Modelling emergency disaster mortality around the world: a network-based distributional inference approach" by Paolo Pagnottoni, Nicoló Pecora (U. Cattolica of Piacenza) and Alessandro Spelta (U. di [bsky, 0 points, 1 comments]